US5262789A  Source identification system for closely separated spatial sources  Google Patents
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 US5262789A US5262789A US07876957 US87695792A US5262789A US 5262789 A US5262789 A US 5262789A US 07876957 US07876957 US 07876957 US 87695792 A US87695792 A US 87695792A US 5262789 A US5262789 A US 5262789A
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 H—ELECTRICITY
 H01—BASIC ELECTRIC ELEMENTS
 H01Q—AERIALS
 H01Q3/00—Arrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an aerial or aerial system
 H01Q3/22—Arrangements for changing or varying the orientation or the shape of the directional pattern of the waves radiated from an aerial or aerial system varying the orientation in accordance with variation of frequency of radiated wave

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 G01—MEASURING; TESTING
 G01S—RADIO DIRECTIONFINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCEDETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
 G01S3/00—Directionfinders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received
 G01S3/02—Directionfinders for determining the direction from which infrasonic, sonic, ultrasonic, or electromagnetic waves, or particle emission, not having a directional significance, are being received using radio waves
 G01S3/74—Multichannel systems specially adapted for directionfinding, i.e. having a single aerial system capable of giving simultaneous indications of the directions of different signals
Abstract
Description
Reference is made to related application "SMALL TARGET DOPPLER DETECTION SYSTEM" Seth David Silverstein and Robert L. Nevin Ser. No. 876,958 filed simultaneously with this application and assigned to the present assignee.
1. Field of the Invention
The invention relates to phased array detection systems and radio communications systems.
2. Description of Related Art
Phased arrays are used in radar systems to receive electromagnetic signals that are transmitted from or reflected from objects at a distance. Phased array systems employ a plurality of sensors distributed over a surface which detects the electromagnetic signals from the sources. Array geometries can be either one or two dimensional. Cellular telephone systems may employ phased arrays to receive signals emanated from distant transmitters. Ultrasound imaging systems may employ phase array receiver to locate reflected ultrasound. In a digital phased array system, the signals incident upon the phased array are sampled and digitized at successive instants in time for each of the sensor elements. The digitized signals are processed in order to produce solutions estimating the direction of arrival (DOA) of signals transmitted or reflected from the sources.
The digital signals detected by the sensors can be processed by superresolution analyzers. Superresolution analyzers in the spatial domain solve for the direction of incoming narrow band signals from sources that have small angular separations, usually less than a Rayleigh resolution. The Rayleigh resolution for a narrow band electromagnetic signal of central wavelength λ, incident on a linear array of length L, is given by λ/L. For a linear array with M elements each separated by λ/2 the Rayleigh angular resolution is δθ≈2/M.
Significant advances have been made in recent years in the development of superresolution analyzers employing phased arrays that can accurately estimate the DOA of point sources. Electromagnetic or acoustic waves arising from distant sources behave as plane waves incident upon the array. Near optimal performance results for the DOA estimates are exhibited by the subspace array processing algorithms such as, for example, the MUSIC algorithm (See "Multiple Emitter Location and Signal Parameter Estimation", R. O. Schmidt, IEEE Trans. Antennas and Propagation, Vol. AP34, pp. 276280, March 1986), the RootMUSIC algorithm, (See "The Mathematical Basis for Element and Fourier Beam Space MUSIC and RootMUSIC Algorithms", S. D. Silverstein and M. D. Zoltowski, Digital Signal Processing, Vol. 1 pp. 161175, July 1991), and the ESPRIT alogorithm (See "ESPRITA Subspace Rotational Approach to Signal Parameter Estimation", R. Roy, A. Paulraj, and T. Kailath, IEEE Trans. Acoust. Speech Signal Process vol. ASSP34, pp. 13401342, October 1986).
Although the present superresolution analyzer compute the DOA of sources, they do not compute their relative signal strengths or the signal to noise ratios of the sources. In radar applications this information may be useful in reducing false alarms in the identification of real targets. This information is especially important for discerning sources that emit signals of relative low power that have bearing angles that are in close proximity to the bearing angles of sources that emit signals of relative high power such as electronic countermeasure jammers.
In communication applications, it is important to know both the DOA and relative powers of communicating sources to select the correct source to decode a proper message.
Currently, there is a need for a method that determines both the DOA of sources as well as their relative signal strengths.
A source identification system identifies proper sources by estimating the direction of arrival (DOA) angles and the signal to noise ratios of a number of distant radiation sources or objects reflecting transmitted radiation. A spatial phased array senses a signal from the sources. The sensed signal represents a superposition of signals of varying power sources. At successive intervals of time the signal incident upon the phased array is sampled and digitized for each of the sensor elements. A complete set of data taken at a given instant across the whole array is referred to as a "snapshot" of the signal. Data from each sensor element value is captured for a number of uncorrelated snapshots. A covariance generation unit constructs a sample covariance matrix from the data from all the sensors over a number of uncorrelated snapshots. For an array with M elements, the sample covariance matrix will be an M×M matrix. An eigenanalysis processor generates a set of eigenvectors and eigenvalues from the sample covariance matrix. This results in two orthogonal subspaces referred to as a signal subspace and a noise subspace. The sources can be represented as vectors. These source vectors are primarilly contained within the signal subspace, hence they are approximately orthogonal to the noise subspace and may be separated. Once they are separated, the relative powers of the sources may be determined. A source number estimator determines the number of sources from the eigenvectors. A DOA processor estimates DOA for the number of sources by employing a superresolution algorithm. A power estimation processor performs analysis based upon the effects of fluctuations due to finite data sampling on the sample covariance matrix. A target detection logic unit identifies sources to be tracked based upon the DOA and signal to noise ratio of the source. A signal synthesis and decoding unit processes the identified signals and suppresses undesired sources for presentation on an output device.
The present invention provides a measure of the relative power of sources along with their bearing angles allowing identification of sources such as relatively low power coherent sources in the presence of other coherent sources of relatively large signal power. This commonly is the situation in radar systems when high power sources corresponding to signal countermeasure (jammers) are applied to mask low power sources corresponding to targets.
It is an object of the present invention to provide an estimation of the relative powers of signals from distant sources.
It is another object of the present invention to determine the direction of arrival and identify low power sources that are in close bearing angle proximity to sources that have much larger powers.
It is another object of the present invention to determine the direction of arrival and identify low power sources that are in close bearing angle proximity to electronic countermeasure jammers.
It is another object of the present invention to use direction of arrival information and signal to noise ratio estimates for selection of specific communication sources in a communication system.
The features of the invention believed to be novel are set forth with particularity in the appended claims. The invention itself, however, both as to organization and method of operation, together with further objects and advantages thereof, may best be understood by reference to the following description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a block diagram of a source identification system according to the present invention.
FIG. 2 illustrates the received direction of arrival of two electromagnetic signals received by a phased array from two sources having bearing angles θ_{1} and θ_{2}.
FIG. 3 is a logarithmic graph of statistical results for power estimates of two sources that differ in their signal to noise ratio by 40 dB as a function of the snapshot number.
FIG. 4 is a logarithmic graph of statistical results for power estimates of two sources that differ in their signal to noise ratio by 40 dB as a function of angular separation in units of the Rayleigh resolution.
A source identification system shown in FIG. 1 estimates the power of transmitted or reflected signals from a number of remote sources incident upon a phased array 10 having M elements. In the preferred embodiment, the superresolution analyzer is a pulsed radar system where radiation is transmitted as narrow band signals having modulation bandwidths Δω that are small compared to the carrier frequencies, ω_{c}, i.e., Δω/ω_{c} <<1. In pulsed radar systems, a radiation pulse is transmitted toward a number of sources allowing enough time for the transmitted radiation to reach a number of sources to be identified, and reflect back to the system before transmitting a subsequent radiation pulse. The spacing between array sensor elements 10 are set at 1/2 the carrier wavelength (λ_{c}). Incident radiation transmitted from, or reflected from two distant coherent sources shown in FIG. 2 have bearing angles θ_{1}, θ_{2}, relative to the phased array 10. Phased array sensors 10 create coherent signals upon receiving radiation from the sources. This signal is sampled at the array at specific instants of time t_{l} . In FIG. 1, each sample is individually modulated down to baseband by a demodulator 20 and digitized by an analogtodigital (A/D) converter 30 to a value x_{l} (n) where n is an index representing a sensor 10, and l is an index representing the snapshot number taken after the lth time interval. A set of digitized samples for all sensors of the phased array is called a "snapshot". For a pulsed radar, the snapshot interval is equal to the reciprocal of the pulse repetition frequency. For most situations the pulse intervals will be sufficiently long for the snapshots to be at least partially decorrelated. The decorrelation of the emitter signals from snapshot to snapshot is physically brought about the motion of the emitter source in the time interval between the snapshots. If the source moves by a distance that is the order of the carrier wavelength or larger in the time period between snapshots, a random phase will be associated with the captured snapshot signals. The decorrelation nature of these phases establishes the decorrelation of the signals.
The digitized values lth snapshot can be conveniently stored in a vector format as:
x.sub.l =[x.sub.l (0), x.sub.t (1) . . . x.sub.l (M1)]. (1)
The M components of x_{l} correspond to the complex representation of the signal received at time interval l. Values from multiple snapshots are accumulated by a snapshot storage unit 40 and each digitized value separately stored in a data matrix X_{N} within snapshot storage unit 40, where the columns of the data matrix correspond to the individual snapshot vectors x_{l}.
Each of the signals received by the phased array conveys information about the physical parameters of the source. The physical parameters of interest in this invention are the DOA angles and the mean powers of the signals from the emitting sources. The signals received at the array sensor elements are different for different uncorrelated snapshots. This difference is due to the fact that some physical processes that influence the received signals vary in time in a random statistical manner. Accordingly, the physical parameters of interest such as DOA angles and signal to noise ratio of the sources are statistical quantities that must be determined by statistical estimation techniques. In statistical analyses, the data corresponding to random processes is accumulated in a digital format and cross correlated to extract the desired statistical information. The cross correlation of the data is usually organized in matrix format known as a sample covariance matrix.
Covariance generation unit 50 manipulates digitized values of the data matrices X_{N} to produce products referred to in the art as the matrix outer product. For N snapshots, the sample covariance matrix R_{N} is a Hermitian matrix having M×M individual matrix elements where M is the number of phased array sensors 10, and R_{N} (m, n) corresponds to the mth row and nth column given by: ##EQU1## where x_{l} ^{*} (n) represents the complex conjugate of the digitized values x_{l} (n). The matrix elements of the sample covariance matrix R_{N} for N snapshots are constructed from the average of the corresponding matrix elements all the individual snapshot autocorrelation matrices.
The information necessary to obtain the most probable value of the physical parameters is contained in the structure of the sample covariance. This information can be extracted by a variety of algorithmic techniques that typically utilize some aspect of the mathematical eigenstructure of the sample covariance matrix. An Mth order covariance matrix will possess M eigenvectors such that the product of the matrix with one of its eigenvectors produces a constant times the eigenvector. The constant is known as an eigenvalue of the matrix corresponding to the specific eigenvector. All the eigenvectors in a matrix multiplication sense are orthogonal to each other.
Eigenanalysis processor 60 then performs eigenanalysis on the sample covariance matrix. For an Mth order array, the M×M sample covariance matrix will have M eigenvectors that satisfy the matrix equation,
R.sub.N e.sub.k =λ.sub.k e.sub.k. (3)
Here λ_{1} ≧ . . . λ_{M} are the eigenvalues and e_{1}, . . . , e_{m} are the corresponding eigenvectors of R_{N}. The eigenvectors of R_{N} are an orthonormal set of basis vectors, e_{m} ^{H} e_{n} =δ_{mn}. For an infinite number of decorrelated snapshots, eigenvectors e_{1}, . . . , e_{M} of the asymptotic form of sample covariance matrix R_{N} can be divided into two orthogonal subspaces referred to as the signal and noise subspaces. The signal subspace has dimension d corresponding to the d sources, while the orthogonal noise subspace will have dimension Md. For an infinite number of snapshots, the noise subspace eigenvalues will all be equal to σ^{2}, the average noise power per element.
A source number estimator 75 received the eigenvectors and eigenvalues from eigenanalysis processor 60 and determines the number of sources d. Source number estimator 75 may determine the number of sources according to a source order estimation algorithm well known in the art such as described in "Detection of Signals by Information Theoretic Criteria", M. Wax and T. Kailath, IEEE Trans ASSP, Vol. 33, pp. 387392, April 1985.
A set of signal vectors from all possible sources that can be received by phased array 10 is referred to in the art as the "array manifold". There is a distinct vector in array manifold a(θ) for every possible direction of arrival angle θ. As there are an infinite number of possible direction of arrival angles, there are an infinite number of array manifold vectors in the array manifold. For a situation with d real uncorrelated sources, with specific direction of arrival bearing angles, θ_{1}, θ_{2} . . . θ_{d} there are d source array manifold vectors, a(θ_{1}), . . . , a(θ_{d}), contained within the total array manifold.
In the limit of an infinite number of decorrelated snapshots, the d source array manifold vectors lie entirely within the signal subspace and are orthogonal to the noise subspace. For a finite number of snapshots, the source array manifold vectors are only approximately orthogonal to the noise subspace.
A DOA processor 80 employs a conventional DOA estimation techniques such as, for example, MUSIC, Root MUSIC, or ESPRIT to determine the direction of arrival from the number of sources d and the eigenvalues and eigenvectors. DOA processor 80 estimates the DOA angles by finding the d specific array manifold vectors that are most orthogonal to the noise subspace. Once the DOA angles are accurately estimated, a set of array manifold vectors, each corresponding to a source, are created by DOA processor 80. For d sources with DOA angles θ_{1}, θ_{2} . . . θ_{d}, the d source array manifold vectors contained within the total array manifold have the functional form: ##EQU2## with z_{q} ^{i} =e^{j2}πqf.sbsp.i where q=0, 1, . . . , M1. The spatial frequencies of the sources, f_{i}, are defined in terms of the source bearing angles by
f.sub.i ≡1/2sin (θ.sub.i).
For finite snapshot numbers, the explicit functional dependence on the system parameters of the finite projections of the source array manifold vectors a(θ_{i}) onto the noise subspace provides the necessary information to determine the relative source powers. A power estimation processor 70 performs computational analysis based upon fundamental considerations of the effects of fluctuations due to finite data samples on the mathematical structure of sample covariance matrix R_{N}. DOA processor 80 creates a frequency spectrum that is equal to the reciprocal of the square of the value of the projection of the array manifold vectors a(θ_{i}) onto the noise subspace eigenvectors e_{k}. The nonorthogonality of the source array manifold vectors a(θ_{i}) for finite number of sources implies that the values of the frequency spectrum at the source spatial frequencies will be finite.
For signals from d sources received by an M element phased array, the frequency spectrum S(θ_{i}) evaluated at accurate DOA estimates {θ_{i} }, approximately fits the relation: ##EQU3##
Here N is the number of uncorrelated snapshots; ##EQU4## are the mean values of the source powers represented by their signal to noise ratios; and σ^{2} is the noise power per receiver element. Power estimation processor 70 estimates the power directly by fitting the value of the frequency spectrum calculated from the data to the functional relation given by Eq. 5.
Power estimation processor 70 estimates the signal to noise ratio of the sources by projecting the source array manifold vectors a(θ_{1}), a(θ_{2}) . . . a(θ_{d}) onto each corresponding approximate noise subspace eigenvector e_{k} of sample covariance matrix R_{N} where k>d. The square magnitude of this projection is represented by D(θ_{i}), ##EQU5## where D(θ_{i}) is the reciprocal of the frequency spectrum, ##EQU6## Power estimation processor 70 calculates the projection of the estimated source array manifold vectors a(θ_{i}) onto the approximate noise subspace eigenvectors e_{k} of the sample covariance matrix R_{N}. Since ##EQU7## can be derived from Eq. 6, the estimated signal to noise ratios of the sources ##EQU8## follows directly from Eq. (6), using the stored calculated values of the array manifold a(θ_{i}) vectors and the approximate noise eigenvectors e_{k}. Here, ##EQU9##
In an alternative embodiment, power estimation processor 70 can estimate the signal powers using a subset of the noise subspace. For example, for any single noise eigenvector one can use the approximate relation: ##EQU10##
A target detection unit 90 receives the array vectors a(θ_{i}) indicating the DOA of each source, and the power of each source P(θ_{i}) from DOA processor 80 and power estimation processor 70, respectively. Target detection unit 90 determines which sources to track, and which sources to ignore based upon its input. For example, the power of a reflected radar signal from a bird will usually be considerably lower than the echo from an aircraft at a comparable range. Also electronic countermeasure jammers transmit significantly greater power than a target. Target detection unit 90 separates the signal which are to be tracked from those that are to be ignored, and passed the tracked signals onto a signal synthesis and decoding unit 100 which decodes the tracked signal and creates a display signal. An output device 110 may be a radar monitor which displays an image of the tracked sources for a user to view and analyze.
In the case of the present invention being employed in cellular telephone systems, each source transmits radiation signals instead of reflecting radiation incident upon them. A base station may keep track of the relative powers of mobile units and transmit accordingly to each in order to transmit a signal which may be easily received without overmodulating. Target detection unit 90 chooses a signal from a mobile unit that it is currently communicating with, and passes that signal to signal synthesis and decoding unit 100 which creates an audio signal and drives output device 110 such as a speaker system.
Output device 110 may alternatively be a digital computer that further processes the received signal, or a control device to actuate mechanisms such as navigational equipment on a ship to move the ship relative to the sensed sources.
In alternative embodiments signal synthesis and decoding unit 100 and output devices 110 will vary according to the intended use.
A simulation was conducted using the present invention as it would be employed in a radar system. A 16 element phased array with element spacing set at 1/2 the carrier wavelength was employed. The Rayleigh spatial frequency resolution for this array is equal to (1/16). The DOA angles are estimated using the RootMUSIC algorithm which is capable of accurate DOA estimates of sources that differ by large amount of power. The power estimates in these simulations are made using the approximate relation described by Eq. 7 above.
FIG. 3 is a logarithmic graph of statistical results for power estimates employing the present invention as a function of the number of snapshots for the specific case of two point sources detected by the 16 element spatial phased array. The point source model is a good representation for radar targets or rf communication sources such as a cellular telephone source. The two sources have SNRs of 40 and 0 dB, and are separated in spatial frequency by 1/2 of the Rayleigh spatial frequency resolution. Statistics were accumulated using 100 independent runs for each of the snapshot orders indicated by the data points in the figures. The solid line represents the actual power values, circles signify the estimated mean calculated with the present invention and crosses signify the range of the standard deviation of the estimated means. An important aspect of the present invention is that the power estimates are accurate for a relatively small numbers of snapshots, down to approximately 10 snapshots.
FIG. 4 is a logarithmic graph of statistical estimation results employing the present invention for two sources at variable angular separations. The source power levels are 40 and 0 dB. The weaker source estimates exhibits some deterioration, when source separations are less than 0.3 Rayleigh units.
Another simulation was performed with the simulation results given in Table 1 below.
TABLE 1__________________________________________________________________________Simulation ResultsSpatial Frequencies Source Powers dB Calculated Powers dB__________________________________________________________________________5/16 5.5/16 6.3/16 80 0 50 80 2.4 505/16 5.5/16 6.3/16 60 0 0 60 3.2 2.65/16 5.5/16 6.3/16 0 0 0 3.6 3.6 2.35/16 5.5/16 6.2/16 3.5/16 50 0 20 0 50 2.5 20 1.25/16 5.5/16 6.2/16 3.5/16 50 10 30 10 50 9.5 30 9.65/16 5.5/16 6.2/16 3.5/16 70 0 40 10 70 2.3 40 9.9__________________________________________________________________________
The top three rows of Table 1 are power estimate simulation results for three sources of differing power. The bottom three rows of Table 1 are power estimate simulation results for four sources of differing power. These simulations have been made with the 16 element linear array. The power estimates shown in the third column are excellent for high SNR sources. Low SNR source values exhibit some negative biasing effects, but may be used to identify different sources.
While several presently preferred embodiments of the invention have been described in detail herein, many modifications and variations will now become apparent to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and variations as fall within the true spirit of the invention.
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R.sub.N e.sub.k =λ.sub.k e.sub.k
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US5815116A (en) *  19951129  19980929  Trw Inc.  Personal beam cellular communication system 
US5828658A (en) *  19911212  19981027  Arraycomm, Inc.  Spectrally efficient high capacity wireless communication systems with spatiotemporal processing 
US5859610A (en) *  19940616  19990112  Alcatel N.V.  Method and a system for locating ground equipment transmitting via satellites 
US6043770A (en) *  19981023  20000328  The United States Of America As Represented By The Secretary Of The Navy  Statistical inference of electromagnetic interference sources based on a priori knowledge of source and receiver parameters 
US6104345A (en) *  19980409  20000815  State Of Israel, Ministry Of Defense Armament Development AuthorityRafael  Direction of arrival tracking of multiple targets 
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US6225948B1 (en) *  19980325  20010501  Siemens Aktiengesellschaft  Method for direction estimation 
FR2806499A1 (en) *  20000320  20010921  Thomson Csf  Method for estimating a correlation matrix of interfering signals received by a sensor array 
US6349218B1 (en) *  19980122  20020219  Matsushita Electric Industrial Co., Ltd.  Adaptive array antenna system and mobile telecommunications system using the same 
EP1215507A2 (en) *  20001212  20020619  Matsushita Electric Industrial Co., Ltd.  Radiowave arrivaldirection estimating apparatus and directional variable transceiver 
US6463295B1 (en)  19961011  20021008  Arraycomm, Inc.  Power control with signal quality estimation for smart antenna communication systems 
US6498581B1 (en)  20010905  20021224  Lockheed Martin Corporation  Radar system and method including superresolution raid counting 
US6505053B1 (en)  19991105  20030107  At&T Corp.  Method for sinusoidal modeling and prediction of fast fading processes 
WO2003023436A2 (en) *  20010907  20030320  Lockheed Martin Corporation  Adaptive digital beamforming radar method 
US20030063029A1 (en) *  20000225  20030403  Anne Ferreol  Method for locating radioelectric sources using twochannel high resolution radiogoniometer 
US6549762B1 (en) *  19990106  20030415  Nec Corporation  Method for estimating arrival direction of desired wave 
US6567034B1 (en)  20010905  20030520  Lockheed Martin Corporation  Digital beamforming radar system and method with superresolution multiple jammer location 
US6600914B2 (en)  19990524  20030729  Arraycomm, Inc.  System and method for emergency call channel allocation 
US6615024B1 (en)  19980501  20030902  Arraycomm, Inc.  Method and apparatus for determining signatures for calibrating a communication station having an antenna array 
WO2003079045A2 (en) *  20020313  20030925  Raytheon Canada Limited  System and method for spectral generation in radar 
US6690747B2 (en)  19961011  20040210  Arraycomm, Inc.  Method for reference signal generation in the presence of frequency offsets in a communications station with spatial processing 
US6717979B2 (en) *  20010427  20040406  Mitsubishi Electric Information Technology Centre Europe B.V.  Method for estimating a direction of arrival 
US6795409B1 (en)  20000929  20040921  Arraycomm, Inc.  Cooperative polling in a wireless data communication system having smart antenna processing 
US6839573B1 (en)  19990607  20050104  Arraycomm, Inc.  Apparatus and method for beamforming in a changinginterference environment 
US6894630B1 (en) *  19991102  20050517  The Commonwealth Of Australia  Enhanced direct digitizing array arrangement 
US20050285788A1 (en) *  20030522  20051229  Jingmin Xin  Technique for directionofarrival estimation without eigendecomposition and its application to beamforming at base station 
US6982968B1 (en)  20000929  20060103  Arraycomm, Inc.  Nondirectional transmitting from a wireless data base station having a smart antenna system 
US6983127B1 (en) *  20010731  20060103  Arraycomm, Inc.  Statistical calibration of wireless base stations 
US6985466B1 (en)  19991109  20060110  Arraycomm, Inc.  Downlink signal processing in CDMA systems utilizing arrays of antennae 
US20060007043A1 (en) *  20030625  20060112  Jingmin Xin  Method and device for tracking the directionsofarrival of radio waves 
US7062294B1 (en)  20000929  20060613  Arraycomm, Llc.  Downlink transmission in a wireless data communication system having a base station with a smart antenna system 
US7139592B2 (en)  19990621  20061121  Arraycomm Llc  Null deepening for an adaptive antenna based communication station 
US7299071B1 (en)  19971210  20071120  Arraycomm, Llc  Downlink broadcasting by sequential transmissions from a communication station having an antenna array 
US7447276B1 (en) *  20070829  20081104  Harris Corporation  Receiver and method for blind adaptive thresholding using noise estimator 
US20080278368A1 (en) *  20070510  20081113  Mitsubishi Electric Corporation  Frequency modulation radar device 
US20090058717A1 (en) *  20070831  20090305  Kuhn Walter A  Apparatus and methods for detection of multiple targets within radar resolution cell 
US7804445B1 (en) *  20060302  20100928  Bae Systems Information And Electronic Systems Integration Inc.  Method and apparatus for determination of range and direction for a multiple tone phased array radar in a multipath environment 
US8064944B2 (en)  19961011  20111122  Intel Corporation  Power control with signal quality estimation for smart antenna communications systems 
US8224627B2 (en)  20100428  20120717  Mitov Iliya P  Technique for determination of the signal subspace dimension 
US20120206293A1 (en) *  20081210  20120816  U.S Government as represented by the Secretary of the Army  Method and system for forming images by comparing subsets of image data 
EP2508911A1 (en) *  20110404  20121010  Fujitsu Ten Limited  Calculation device for radar apparatus, calculation method and program for calculation method 
US9106286B2 (en)  20000613  20150811  Comcast Cable Communications, Llc  Network communication using diversity 
US9116227B2 (en)  20120222  20150825  Toyota Motor Engineering & Manufacturing North America, Inc.  Hybrid radar integrated into single package 
USRE45775E1 (en)  20000613  20151020  Comcast Cable Communications, Llc  Method and system for robust, secure, and highefficiency voice and packet transmission over adhoc, mesh, and MIMO communication networks 
EP3151028A1 (en) *  20150929  20170405  Rohde & Schwarz GmbH & Co. KG  Direction finder and method for direction finding wherein a quality criterion for the incoming signals is determined 
Citations (2)
Publication number  Priority date  Publication date  Assignee  Title 

US4754282A (en) *  19700325  19880628  The United States Of America As Represented By The Secretary Of The Navy  Improved data analysis system 
US5049795A (en) *  19900702  19910917  Westinghouse Electric Corp.  Multivariable adaptive vibration canceller 
Patent Citations (2)
Publication number  Priority date  Publication date  Assignee  Title 

US4754282A (en) *  19700325  19880628  The United States Of America As Represented By The Secretary Of The Navy  Improved data analysis system 
US5049795A (en) *  19900702  19910917  Westinghouse Electric Corp.  Multivariable adaptive vibration canceller 
NonPatent Citations (10)
Title 

M. Wax and T. Kailath, "Detection of Signals by Information Theoretic Criteria", Apr. 1985, IEEE Trans ASSP, vol. 33, pp. 387392. 
M. Wax and T. Kailath, Detection of Signals by Information Theoretic Criteria , Apr. 1985, IEEE Trans ASSP, vol. 33, pp. 387 392. * 
R. O. Schmidt, "Multiple Emitter Location and Signal Parameter Estimation", Mar. 1986, IEEE Trans. Antennas and Propagation, vol. AP34, pp. 276280. 
R. O. Schmidt, Multiple Emitter Location and Signal Parameter Estimation , Mar. 1986, IEEE Trans. Antennas and Propagation, vol. AP 34, pp. 276 280. * 
R. Roy, A. Paulraj, and T. Kailath, "ESPRITA Subspace Rotational Approach to Signal Parameter Estimation", Oct. 1986, IEEE Trans. Acoust. Speech Signal Process, vol. ASSP34, pp. 13401342. 
R. Roy, A. Paulraj, and T. Kailath, ESPRIT A Subspace Rotational Approach to Signal Parameter Estimation , Oct. 1986, IEEE Trans. Acoust. Speech Signal Process, vol. ASSP 34, pp. 1340 1342. * 
S. D. Silverstein and M. D. Zoltowski, "The Mathematical Basis for Element and Fourier Beam Space MUSIC and RootMUSIC Algorithms", Jul. 1991, Digital Signal Processing, vol. 1, pp. 161175. 
S. D. Silverstein and M. D. Zoltowski, The Mathematical Basis for Element and Fourier Beam Space MUSIC and Root MUSIC Algorithms , Jul. 1991, Digital Signal Processing, vol. 1, pp. 161 175. * 
U.S. Patent Application, "Small Target Doppler Detection System", Seth David Silverstein and Robert L. Nevin, Ser. No. 876,958 filed Apr. 30, 1992. 
U.S. Patent Application, Small Target Doppler Detection System , Seth David Silverstein and Robert L. Nevin, Ser. No. 876,958 filed Apr. 30, 1992. * 
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US5592490A (en) *  19911212  19970107  Arraycomm, Inc.  Spectrally efficient high capacity wireless communication systems 
US5828658A (en) *  19911212  19981027  Arraycomm, Inc.  Spectrally efficient high capacity wireless communication systems with spatiotemporal processing 
WO1995003552A1 (en) *  19930721  19950202  ESystems, Inc.  Robust multiple cochannel emitter detectors 
US5859610A (en) *  19940616  19990112  Alcatel N.V.  Method and a system for locating ground equipment transmitting via satellites 
EP0804858A4 (en) *  19950120  19990414  Arraycomm Inc  Spectrally efficient high capacity wireless communication systems 
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US5815116A (en) *  19951129  19980929  Trw Inc.  Personal beam cellular communication system 
US6690747B2 (en)  19961011  20040210  Arraycomm, Inc.  Method for reference signal generation in the presence of frequency offsets in a communications station with spatial processing 
US6463295B1 (en)  19961011  20021008  Arraycomm, Inc.  Power control with signal quality estimation for smart antenna communication systems 
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US7299071B1 (en)  19971210  20071120  Arraycomm, Llc  Downlink broadcasting by sequential transmissions from a communication station having an antenna array 
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US6615024B1 (en)  19980501  20030902  Arraycomm, Inc.  Method and apparatus for determining signatures for calibrating a communication station having an antenna array 
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US6963742B2 (en)  19980501  20051108  Arraycomm, Inc.  Periodic calibration on a communications channel 
US6654590B2 (en)  19980501  20031125  Arraycomm, Inc.  Determining a calibration function using at least one remote terminal 
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US6549762B1 (en) *  19990106  20030415  Nec Corporation  Method for estimating arrival direction of desired wave 
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US6505053B1 (en)  19991105  20030107  At&T Corp.  Method for sinusoidal modeling and prediction of fast fading processes 
US6658261B1 (en)  19991105  20031202  At&T Corp.  Method for sinusoidal modeling and prediction of fast fading processes 
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US20030020650A1 (en) *  20000320  20030130  Pascal Chevalier  Method for estimating correlation matrix of interfering signals received through a sensor array 
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WO2001071548A1 (en) *  20000320  20010927  Thales  Method for estimating a correlation matrix of interfering signals received through a sensor array 
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US7062294B1 (en)  20000929  20060613  Arraycomm, Llc.  Downlink transmission in a wireless data communication system having a base station with a smart antenna system 
US6982968B1 (en)  20000929  20060103  Arraycomm, Inc.  Nondirectional transmitting from a wireless data base station having a smart antenna system 
US6795409B1 (en)  20000929  20040921  Arraycomm, Inc.  Cooperative polling in a wireless data communication system having smart antenna processing 
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US6642888B2 (en)  20001212  20031104  Matsushita Electric Industrial Co., Ltd.  Radiowave arrivaldirection estimating apparatus and directional variable transceiver 
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US6836245B2 (en)  20001212  20041228  Matsushita Electric Industrial Co., Ltd.  Radiowave arrivaldirection estimating apparatus and directional variable transceiver 
US20040189523A1 (en) *  20001212  20040930  Takaaki Kishigami  Radiowave arrivaldirection estimating apparatus and directional variable transceiver 
US20040027282A1 (en) *  20001212  20040212  Takaaki Kishigami  Radiowave arrivaldirection estimating apparatus and directional variable transceiver 
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US6717979B2 (en) *  20010427  20040406  Mitsubishi Electric Information Technology Centre Europe B.V.  Method for estimating a direction of arrival 
US6983127B1 (en) *  20010731  20060103  Arraycomm, Inc.  Statistical calibration of wireless base stations 
US6567034B1 (en)  20010905  20030520  Lockheed Martin Corporation  Digital beamforming radar system and method with superresolution multiple jammer location 
US6498581B1 (en)  20010905  20021224  Lockheed Martin Corporation  Radar system and method including superresolution raid counting 
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US6653973B2 (en)  20010907  20031125  Lockheed Martin Corporation  Adaptive digital beamforming radar method and system for maintaining multiple source angle superresolution capability in jamming 
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US6822606B2 (en)  20020313  20041123  Raytheon Canada Limited  System and method for spectral generation in radar 
WO2003079045A2 (en) *  20020313  20030925  Raytheon Canada Limited  System and method for spectral generation in radar 
WO2003079045A3 (en) *  20020313  20031204  Raytheon Co  System and method for spectral generation in radar 
US7068221B2 (en) *  20030522  20060627  Fujitsu Limited  Technique for directionofarrival estimation without eigendecomposition and its application to beamforming at base station 
US20050285788A1 (en) *  20030522  20051229  Jingmin Xin  Technique for directionofarrival estimation without eigendecomposition and its application to beamforming at base station 
US20060007043A1 (en) *  20030625  20060112  Jingmin Xin  Method and device for tracking the directionsofarrival of radio waves 
US7084812B2 (en) *  20030625  20060801  Fujitsu Limited  Method and device for tracking the directionsofarrival of radio waves 
US7804445B1 (en) *  20060302  20100928  Bae Systems Information And Electronic Systems Integration Inc.  Method and apparatus for determination of range and direction for a multiple tone phased array radar in a multipath environment 
US20080278368A1 (en) *  20070510  20081113  Mitsubishi Electric Corporation  Frequency modulation radar device 
US7532154B2 (en) *  20070510  20090512  Mitsubishi Electric Corporation  Frequency modulation radar device 
US7447276B1 (en) *  20070829  20081104  Harris Corporation  Receiver and method for blind adaptive thresholding using noise estimator 
US7535408B2 (en) *  20070831  20090519  Lockheed Martin Corporation  Apparatus and methods for detection of multiple targets within radar resolution cell 
US20090058717A1 (en) *  20070831  20090305  Kuhn Walter A  Apparatus and methods for detection of multiple targets within radar resolution cell 
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